Results 11 to 20 of about 7,291,916 (317)

Prediction of Progression to Severe Stroke in Initially Diagnosed Anterior Circulation Ischemic Cerebral Infarction

Frontiers in Neurology, 2021
Purpose: Accurate prediction of the progression to severe stroke in initially diagnosed nonsevere patients with acute–subacute anterior circulation nonlacuna ischemic infarction (ASACNLII) is important in making clinical decision.
Lai Wei, Yidi Cao, Yidi Cao, Kangwei Zhang, Yun Xu, Xiang Zhou, Jinxi Meng, Aijun Shen, Jiong Ni, Jing Yao, Lei Shi, Lei Shi, Qi Zhang, Qi Zhang, Qi Zhang, Peijun Wang   +15 more
doaj   +1 more source

QubitE:Qubit Embedding for Knowledge Graph Completion [PDF]

Jisuanji kexue, 2023
The knowledge graph completion task completes the knowledge graph by predicting missing facts in the knowledge graph.The quantum-based knowledge graph embedding(KGE) model uses variational quantum circuits to score triples by mea-suring the probability ...
LIN Xueyuan, E Haihong , SONG Wenyu, LUO Haoran, SONG Meina
doaj   +1 more source

Development and Evaluation of a Leukemia Diagnosis System Using Deep Learning in Real Clinical Scenarios

Frontiers in Pediatrics, 2021
Leukemia is the most common malignancy affecting children. The morphologic analysis of bone marrow smears is an important initial step for diagnosis. Recent publications demonstrated that artificial intelligence is able to classify blood cells but a long
Min Zhou, Min Zhou, Kefei Wu, Kefei Wu, Lisha Yu, Mengdi Xu, Mengdi Xu, Junjun Yang, Qing Shen, Qing Shen, Bo Liu, Bo Liu, Lei Shi, Lei Shi, Shuang Wu, Shuang Wu, Bin Dong, Hansong Wang, Hansong Wang, Jiajun Yuan, Jiajun Yuan, Shuhong Shen, Liebin Zhao, Liebin Zhao   +23 more
doaj   +1 more source

DiffKG: Knowledge Graph Diffusion Model for Recommendation [PDF]

Web Search and Data Mining, 2023
Knowledge Graphs (KGs) have emerged as invaluable resources for enriching recommendation systems by providing a wealth of factual information and capturing semantic relationships among items.
Ya Jiang, Yuhao Yang, Lianghao Xia, Chao Huang   +3 more
semanticscholar   +1 more source

Longitudinal trajectories of pneumonia lesions and lymphocyte counts associated with disease severity among convalescent COVID-19 patients: a group-based multi-trajectory analysis

BMC Pulmonary Medicine, 2021
Background To explore the long-term trajectories considering pneumonia volumes and lymphocyte counts with individual data in COVID-19. Methods A cohort of 257 convalescent COVID-19 patients (131 male and 126 females) were included.
Nannan Shi, Chao Huang, Qi Zhang, Chunzi Shi, Fengjun Liu, Fengxiang Song, Qinguo Hou, Jie Shen, Fei Shan, Xiaoming Su, Cheng Liu, Zhiyong Zhang, Lei Shi, Yuxin Shi   +13 more
doaj   +1 more source

Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer

Nature Communications, 2022
Resistance to EGFR inhibitors presents a major obstacle in treating non-small cell lung cancer. Here, the authors develop a recommender system ranking genes based on trade-offs between diverse types of evidence linking them to potential mechanisms of ...
Anna Gogleva, Dimitris Polychronopoulos, Matthias Pfeifer, Vladimir Poroshin, Michaël Ughetto, Matthew J. Martin, Hannah Thorpe, Aurelie Bornot, Paul D. Smith, Ben Sidders, Jonathan R. Dry, Miika Ahdesmäki, Ultan McDermott, Eliseo Papa, Krishna C. Bulusu   +14 more
doaj   +1 more source

GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph [PDF]

Neural Information Processing Systems, 2023
Adapter-style efficient transfer learning (ETL) has shown excellent performance in the tuning of vision-language models (VLMs) under the low-data regime, where only a few additional parameters are introduced to excavate the task-specific knowledge based ...
Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang   +5 more
semanticscholar   +1 more source

A Survey on Multimodal Knowledge Graphs: Construction, Completion and Applications

Mathematics, 2023
As an essential part of artificial intelligence, a knowledge graph describes the real-world entities, concepts and their various semantic relationships in a structured way and has been gradually popularized in a variety practical scenarios.
Yong Chen, Xinkai Ge, Shengli Yang, Linmei Hu, Jie Li, Jinwen Zhang   +5 more
doaj   +1 more source

LLM-assisted Knowledge Graph Engineering: Experiments with ChatGPT [PDF]

AI Tomorrow, 2023
Knowledge Graphs (KG) provide us with a structured, flexible, transparent, cross-system, and collaborative way of organizing our knowledge and data across various domains in society and industrial as well as scientific disciplines.
Lars-Peter Meyer, Claus Stadler, Johannes Frey, Norman Radtke, K. Junghanns, R. Meissner, Gordian Dziwis, Kirill Bulert, Michael Martin   +8 more
semanticscholar   +1 more source

A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19)

Scientific Reports, 2021
This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19.
Feng Pan, Lin Li, Bo Liu, Tianhe Ye, Lingli Li, Dehan Liu, Zezhen Ding, Guangfeng Chen, Bo Liang, Lian Yang, Chuansheng Zheng   +10 more
doaj   +1 more source